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10.1371/journal.pone.0250149

http://scihub22266oqcxt.onion/10.1371/journal.pone.0250149
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33878136!8057600!33878136
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suck abstract from ncbi


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pmid33878136      PLoS+One 2021 ; 16 (4): e0250149
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  • Estimating COVID-19 cases in Makkah region of Saudi Arabia: Space-time ARIMA modeling #MMPMID33878136
  • Awwad FA; Mohamoud MA; Abonazel MR
  • PLoS One 2021[]; 16 (4): e0250149 PMID33878136show ga
  • The novel coronavirus COVID-19 is spreading across the globe. By 30 Sep 2020, the World Health Organization (WHO) announced that the number of cases worldwide had reached 34 million with more than one million deaths. The Kingdom of Saudi Arabia (KSA) registered the first case of COVID-19 on 2 Mar 2020. Since then, the number of infections has been increasing gradually on a daily basis. On 20 Sep 2020, the KSA reported 334,605 cases, with 319,154 recoveries and 4,768 deaths. The KSA has taken several measures to control the spread of COVID-19, especially during the Umrah and Hajj events of 1441, including stopping Umrah and performing this year's Hajj in reduced numbers from within the Kingdom, and imposing a curfew on the cities of the Kingdom from 23 Mar to 28 May 2020. In this article, two statistical models were used to measure the impact of the curfew on the spread of COVID-19 in KSA. The two models are Autoregressive Integrated Moving Average (ARIMA) model and Spatial Time-Autoregressive Integrated Moving Average (STARIMA) model. We used the data obtained from 31 May to 11 October 2020 to assess the model of STARIMA for the COVID-19 confirmation cases in (Makkah, Jeddah, and Taif) in KSA. The results show that STARIMA models are more reliable in forecasting future epidemics of COVID-19 than ARIMA models. We demonstrated the preference of STARIMA models over ARIMA models during the period in which the curfew was lifted.
  • |COVID-19/*epidemiology[MESH]
  • |Disease Transmission, Infectious/prevention & control/statistics & numerical data[MESH]
  • |Forecasting[MESH]
  • |Humans[MESH]
  • |Models, Statistical[MESH]
  • |SARS-CoV-2/isolation & purification[MESH]


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